Advanced Numerical Analysis (L.6) (G1110)

15 credits, Level 6

Autumn teaching

This module deepens the second year module Numerical Analysis by providing:

  • analytic insights and computational techniques in iterative methods for linear and nonlinear systems
  • eigenvalue/vector and singular-value problems
  • optimisation and numerical methods for differential equations.

These techniques underpin most modern algorithms of machine learning, data science and scientific computing. The module has both a theoretical and practical component: we learn how to analyse theoretically the algorithms, and gauge their efficiency, alongside their practical coding (in Python or Matlab/Octave) and testing.


100%: Lecture


20%: Coursework (Portfolio, Problem set, Project)
80%: Examination (Unseen examination)

Contact hours and workload

This module is approximately 150 hours of work. This breaks down into about 33 hours of contact time and about 117 hours of independent study. The University may make minor variations to the contact hours for operational reasons, including timetabling requirements.

We regularly review our modules to incorporate student feedback, staff expertise, as well as the latest research and teaching methodology. We’re planning to run these modules in the academic year 2022/23. However, there may be changes to these modules in response to feedback, staff availability, student demand or updates to our curriculum. We’ll make sure to let you know of any material changes to modules at the earliest opportunity.


This module is offered on the following courses: